Perspective piece on the concept of opioid addiction

This perspective piece on opioid addiction resulted from a workshop on enactive approaches to psychopathology our group organized last year. The science of addiction is in desperate need of a better theoretical framework, and we hope to be able to contribute to its development in the coming years.

The Clinical Concept of Opioid Addiction Since 1877: Still Wanting After All These Years

Christian G. Schütz, Susana Ramírez-Vizcaya, and Tom Froese

In 1877, the psychiatrist Edward Levinstein authored the first monograph on opioid addiction. The prevalence of opioid addiction prior to his publication had risen in several countries including England, France and Germany. He was the first to call it an illness, but doubted that it was a mental illness because the impairment of volition appeared to be restricted to opioid use: it was not pervasive, since it did not extend to other aspects of the individuals’ life. While there has been huge progress in understanding the underlying neurobiological mechanisms, there has been little progress in the clinical psychopathology of addiction and in understanding how it relates to these neurobiological mechanisms. A focus on cravings has limited the exploration of other important aspects such as anosognosia and addiction-related behaviors like smuggling opioids into treatment and supporting the continued provision of co-patients. These behaviors are usually considered secondary reactions, but in clinical practice they appear to be central to addiction, indicating that an improved understanding of the complexity of the disorder is needed. We propose to consider an approach that takes into account the embodied, situated, dynamic, and phenomenological aspects of mental processes. Addiction in this context can be conceptualized as a habit, understood as a distributed network of mental, behavioral, and social processes, which not only shapes the addict’s perceptions and actions, but also has a tendency to self-maintain. Such an approach may help to develop and integrate psychopathological and neurobiological research and practice of addictions.

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Editorial introduction to 4E cognition research in Mexico

With the aim of promoting and raising awareness about embodied, embedded, extended, and enactive cognition (4EC) research here in Mexico, Ximena and I organized a special issue on this theme.

In our editorial introduction we show that 4EC research in Mexico has fertile ground to build on, as there are several local traditions that are sympathetic to its core principles:

Grounding 4E Cognition in Mexico: introduction to special issue on spotlight on 4E Cognition research in Mexico

Ximena Gonzalez-Grandón and Tom Froese

Embodied, embedded, extended and enactive (4EC) perspectives on cognition have gained epistemic legitimacy during the last 25 years in the international arena. They have encouraged new ways to understand the mind. Mexico has not been an exception; rather, it has the potential to provide a fertile ground for the development of 4EC perspectives, as shown by the variety of contributions in this special issue. In this editorial introduction, we discuss recent concerns about a lack of coherence in the inter-relations between these perspectives, and we propose that it is more appropriate to view 4EC as an emerging pluralistic research tradition that shares crucial commitments. Furthermore, we show that this pluralistic tradition has been gaining ground in the specific research context of Mexico, because of the country’s distinctive historical, scientific and philosophical development. We finish by describing the promising research potential of the current heterogeneous explanations as evidenced by the papers in this issue.

Talk on the cognitive science of cave art

I have been invited by the social anthropologists of the National School of Anthropology and History of the North of Mexico to visit them in Chihuahua.

I am excited by this opportunity to discuss the enactive approach to social interaction and to see how it can be put into a mutually informing relationship with anthropology.

Paper on how communal ritual makes social hierarchy more effective

Our contribution to the “Special Issue on Social Learning and Cultural Evolution with Cognitive Systems“, edited by Peter Andras and James Borg, has been accepted for publication in the journal Cognitive Systems Research.

Here is the title and abstract. Clicking the title will open a pre-print version.

Modeling collective rule at ancient Teotihuacan as a complex adaptive system: Communal ritual makes social hierarchy more effective

Tom Froese and Linda R. Manzanilla

Experts remain divided about the nature of the sociopolitical system of ancient Teotihuacan, which was one of the earliest and largest urban civilizations of the Americas. Excavations hoping to find compelling evidence of powerful rulers, such as a royal tomb, keep coming away empty-handed. But the alternative possibility of collective rule still remains poorly understood as well. Previously we used a computational model of this city’s hypothetical sociopolitical network to show that in principle collective rule based on communal ritual could be an effective strategy of ensuring widespread social coordination, as long as we assume that the network’s structure could be transformed via social learning and local leaders were not strongly subdivided. Here we extended this model to investigate whether increased social hierarchy could mitigate the negative effects of such strong divisions. We found a special synergy between social hierarchy and communal ritual: only their combination improved the extent of social coordination, whereas the introduction of centralization and top-down influence by themselves had no effect. This finding is consistent with portrayals of the Teotihuacan elite as religious specialists serving the public good, in particular by synchronizing the city’s ritual calendar with the rhythms of the stars.

New paper: Self-Optimization in Continuous-Time Recurrent Neural Networks

We were able to generalize the powerful self-optimization process to continuous-time neural networks, the class of neural networks most used by evolutionary robotics.

Self-Optimization in Continuous-Time Recurrent Neural Networks

Mario Zarco and Tom Froese

A recent advance in complex adaptive systems has revealed a new unsupervised learning technique called self-modeling or self-optimization. Basically, a complex network that can form an associative memory of the state configurations of the attractors on which it converges will optimize its structure: it will spontaneously generalize over these typically suboptimal attractors and thereby also reinforce more optimal attractors—even if these better solutions are normally so hard to find that they have never been previously visited. Ideally, after sufficient self-optimization the most optimal attractor dominates the state space, and the network will converge on it from any initial condition. This technique has been applied to social networks, gene regulatory networks, and neural networks, but its application to less restricted neural controllers, as typically used in evolutionary robotics, has not yet been attempted. Here we show for the first time that the self-optimization process can be implemented in a continuous-time recurrent neural network with asymmetrical connections. We discuss several open challenges that must still be addressed before this technique could be applied in actual robotic scenarios.

Latest issue of Adaptive Behavior!

The latest issue of Adaptive Behavior is out with a nice mix of content.

I picked the article by Julian Kiverstein and Erik Rietveld on “Reconceiving representation-hungry cognition: an ecological-enactive proposal” as my editor’s pick, so it’s available for free!

The problem of meaning in AI: Still with us after all these years

I was invited to give a talk at the “Programs, minds and machines” workshop, which will be hosted jointly by the Mathematics and the Philosophy Research Institutes of UNAM, August 6-9, 2018.

The problem of meaning in AI: Still with us after all these years

Tom Froese

In recent years there has been a lot of excitement about the possibilities of advanced artificial intelligence that could rival the human mind. I cast doubt on this prospect by reviewing past revolutions in cognitive robotics, specifically the shift toward situated robotics in the 90s and the shift toward a dynamical approach in the 00s. I argue that despite claims to the contrary, these revolutions did not manage to overcome the fundamental problem of meaning that was first identified in the context of various theoretical and practical problems faced by Good Old-Fashioned AI. Even after billions of dollars of investment, today’s computers simply do not understand anything. I argue for a paradigm shift in the field: the aim should not be to replicate the human mind in autonomous systems, but to help it realize its full potential via interfaces.

Ritual anti-structure as an alternate pathway to social complexity

I was invited to contribute a short opinion piece to the “In Conversation” section of Material Religion regarding recent insights of cognitive science.

Ritual anti-structure as an alternate pathway to social complexity? The case of ancient Teotihuacan, Central Mexico

Tom Froese

There is growing dissatisfaction with the traditional approach to the evolution of complex societies, which treated it principally as a sequence of transformations toward political centralization driven by the construction of increasingly vertical hierarchies by a powerful elite. In Mesoamerica the evidence is more consistent with a variety of alternative pathways to social complexity, and these are fruitfully approached from theoretical perspectives based on social heterarchy (Crumley 2003), collective action (Fargher et al. 2011), and, so I will suggest, ritual anti-structure (Turner 1969).

An artificial life approach to the origins of the genetic code

I have been invited to give a talk at the “Special workshop: The Earth, Life and Artificial Life”, sponsored by ELSI, which will take place next Friday, July 27, as part of the International Conference on Artificial Life in Tokyo.

The title and abstract are as follows:

An artificial life approach to the origins of the genetic code

Tom Froese

A growing number of artificial life researchers propose that making progress on the problem of the origins of life requires taking seriously life’s embodiment: even very simple life-like systems that are spatially individuated can interact with their environment in an adaptive manner. This behavior-based approach has also opened up new perspectives on a related unsolved problem, namely the origin of the genetic code, which can now be seen as emerging out of iterated interactions in a community of individuals. Thus, artificial life demonstrates that the dominant scientific strategy of searching for the conditions of Darwinian evolution should be broadened to consider other possibilities of optimization.

New article on entraining chaotic dynamics

We show that it is possible for a participant to interactively control a chaotic system by entraining with its dynamics, with the effect that they become more regular while the participant becomes more chaotic.

This has implications both for researchers interested in controlling chaotic systems, and also for practitioners in movement rehabilitation.

Entraining chaotic dynamics: A novel movement sonification paradigm could promote generalization

Dobromir Dotov and Tom Froese

Tasks encountered in daily living may have instabilities and more dimensions than are sampled by the senses such as when carrying a cup of coffee and only the surface motion and overall momentum are sensed, not the fluid dynamics. Anticipating non-periodic dynamics is difficult but not impossible because mutual coordination allows for chaotic processes to synchronize to each other and become periodic. A chaotic oscillator with random period and amplitude affords being stabilized onto a periodic trajectory by a weak input if the driver incorporates information about the oscillator. We studied synchronization with predictable and unpredictable stimuli where the unpredictable stimuli could be non-interactive or interactive. The latter condition required learning to control a chaotic system. We expected better overall performance with the predictable but more learning and generalization with unpredictable interactive stimuli. Participants practiced an auditory-motor synchronization task by matching their sonified hand movements to sonified tutors: the Non-Interactive Predictable tutor (NI-P) was a sinusoid, the Non-Interactive Unpredictable (NI-U) was a chaotic system, the Interactive Unpredictable (I-U) was the same chaotic system with an added weak input from the participant’s movement. Different pre/post-practice stimuli evaluated generalization. Quick improvement was seen in NI-P. Synchronization, dynamic similarity, and causal interaction increased with practice in I-U but not in NI-U. Generalization was seen for few pre-post stimuli in NI-P, none in NI-U, and most stimuli in I-U. Synchronization with novel chaotic dynamics is challenging but mutual interaction enables the behavioral control of such dynamics and the practice of complex motor skills.

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